@InProceedings{moosavi-strube:2017:Short,
author = {Moosavi, Nafise Sadat and Strube, Michael},
title = {Lexical Features in Coreference Resolution: To be Used With Caution},
booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
month = {July},
year = {2017},
address = {Vancouver, Canada},
publisher = {Association for Computational Linguistics},
pages = {14--19},
abstract = {Lexical features are a major source of information in state-of-the-art
coreference resolvers. Lexical features implicitly model some of the linguistic
phenomena at a fine granularity level. They are especially useful for
representing the context of mentions. In this paper we investigate a drawback
of using many lexical features in state-of-the-art coreference resolvers. We
show that if coreference resolvers mainly rely on lexical features, they can
hardly generalize to unseen domains. Furthermore, we show that the current
coreference resolution evaluation is clearly flawed by only evaluating on a
specific split of a specific dataset in which there is a notable overlap
between the training, development and test sets.},
url = {http://aclweb.org/anthology/P17-2003}
}